Christian Eitzinger

Zusammenfassung

Starting from concrete applications of robotic inspection systems in the field of active thermography and surface inspection, the specific computational requirements of the tasks will be identified. From these common concepts will be developed that apply to a wider range of inspection robots. In the second part of the presentation the use of machine learning methods will be presented to show how machine learning is applied in the aesthetic judgment of surfaces and how machine learning is used as an analysis tool to model male and female decision making in quality control applications.

Vortragender

Dr. Christian Eitzinger received his Master degree from the University of Linz in 1995. In 1997 he started working at Profactor as a researcher in the field of image processing and is head of the machine vision group since 2001. He received the Erwin-Wenzl Price for his thesis on training methods for fuzzy neural networks and is member of the Austrian Association for Pattern recognition. Since 2005 he is coordinating several European research projects in the field of machine vision